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Liu Y, Zhang X, Pang Z, Wang Y, Zheng H, Wang G, Wang K, Du J. Prediction of prognosis and immunotherapy efficacy based on metabolic landscape in lung adenocarcinoma by bulk, single-cell RNA sequencing and Mendelian randomization analyses. Aging (Albany NY) 2024; 16:205838. [PMID: 38771130 DOI: 10.18632/aging.205838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 04/16/2024] [Indexed: 05/22/2024]
Abstract
Immunotherapy has been a remarkable clinical advancement in cancer treatment, but only a few patients benefit from it. Metabolic reprogramming is tightly associated with immunotherapy efficacy and clinical outcomes. However, comprehensively analyzing their relationship is still lacking in lung adenocarcinoma (LUAD). Herein, we evaluated 84 metabolic pathways in TCGA-LUAD by ssGSEA. A matrix of metabolic pathway pairs was generated and a metabolic pathway-pair score (MPPS) model was established by univariable, LASSO, multivariable Cox regression analyses. The differences of metabolic reprogramming, tumor microenvironment (TME), tumor mutation burden and drug sensitivity in different MPPS groups were further explored. WGCNA and 117 machine learning algorithms were performed to identify MPPS-related genes. Single-cell RNA sequencing and in vitro experiments were used to explore the role of C1QTNF6 on TME. The results showed MPPS model accurately predicted prognosis and immunotherapy efficacy of LUAD patients regardless of sequencing platforms. High-MPPS group had worse prognosis, immunotherapy efficacy and lower immune cells infiltration, immune-related genes expression and cancer-immunity cycle scores than low-MPPS group. Seven MPPS-related genes were identified, of which C1QTNF6 was mainly expressed in fibroblasts. High C1QTNF6 expression in fibroblasts was associated with more infiltration of M2 macrophage, Treg cells and less infiltration of NK cells, memory CD8+ T cells. In vitro experiments validated silencing C1QTNF6 in fibroblasts could inhibit M2 macrophage polarization and migration. The study depicted the metabolic landscape of LUAD and constructed a MPPS model to accurately predict prognosis and immunotherapy efficacy. C1QTNF6 was a promising target to regulate M2 macrophage polarization and migration.
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Affiliation(s)
- Yong Liu
- Institute of Oncology, Shandong Provincial Hospital, Shandong University, Jinan 250021, Shandong, China
| | - Xiangwei Zhang
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
| | - Zhaofei Pang
- Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
| | - Yadong Wang
- Institute of Oncology, Shandong Provincial Hospital, Shandong University, Jinan 250021, Shandong, China
| | - Haotian Zheng
- Institute of Oncology, Shandong Provincial Hospital, Shandong University, Jinan 250021, Shandong, China
| | - Guanghui Wang
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
- Institute of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
| | - Kai Wang
- Institute of Oncology, Shandong Provincial Hospital, Shandong University, Jinan 250021, Shandong, China
| | - Jiajun Du
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
- Institute of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
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Wu X, Liu P, Wang Q, Sun L, Wang Y. A prognostic model established using bile acid genes to predict the immunity and survival of patients with gastrointestinal cancer. ENVIRONMENTAL TOXICOLOGY 2024. [PMID: 38606991 DOI: 10.1002/tox.24287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/13/2024] [Accepted: 03/31/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND The metabolism of abnormal bile acids (BAs) is implicated in the initiation and development of gastrointestinal (GI) cancer. However, there was a lack of research on the molecular mechanisms of BAs metabolism in GI. METHODS Genes involved in BAs metabolism were excavated from public databases of The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, and Molecular Signatures Database (MSigDB). ConsensusClusterPlus was used to classify molecular subtypes for GI. To develop a RiskScore model for predicting GI prognosis, univariate Cox analysis was performed on the genes in protein-protein interaction (PPI) network, followed by using Lasso regression and stepwise regression to refine the model and to determine the key prognostic genes. Tumor immune microenvironment in GI patients from different risk groups was assessed using the ESTIMATE algorithm and enrichment analysis. Reverse transcription-quantitative real-time PCR (RT-qPCR), Transwell assay, and wound healing assay were carried out to validate the expression and functions of the model genes. RESULTS This study defined three molecular subtypes (C1, C2, and C3). Specifically, C1 had the best prognosis, while C3 had the worst prognosis with high immune checkpoint gene expression levels and TIDE scores. We selected nine key genes (AXIN2, ATOH1, CHST13, PNMA2, GYG2, MAGEA3, SNCG, HEYL, and RASSF10) that significantly affected the prognosis of GI and used them to develop a RiskScore model accordingly. Combining the verification results from a nomogram, the prediction of the model was proven to be accurate. The high RiskScore group was significantly enriched in tumor and immune-related pathways. Compared with normal gastric mucosal epithelial cells, the mRNA levels of the nine genes were differential in the gastric cancer cells. Inhibition of PNMA2 suppressed migration and invasion of the cancer cells. CONCLUSION We distinguished three GI molecular subtypes with different prognosis based on the genes related to BAs metabolism and developed a RiskScore model, contributing to the diagnosis and treatment of patients with GI.
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Affiliation(s)
- Xin Wu
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Peifa Liu
- Pathology Department, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Qing Wang
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Linde Sun
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Yu Wang
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
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Zhang H, Ma S, Wang Y, Chen X, Li Y, Wang M, Xu Y. Development of an obesity-related multi-gene prognostic model incorporating clinical characteristics in luminal breast cancer. iScience 2024; 27:109133. [PMID: 38384850 PMCID: PMC10879711 DOI: 10.1016/j.isci.2024.109133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/13/2023] [Accepted: 02/01/2024] [Indexed: 02/23/2024] Open
Abstract
Despite adjuvant chemotherapy and endocrine therapy in luminal breast cancer (LBC), relapses are common. Addressing this, we aim to develop a prognostic model to refine adjuvant therapy strategies, particularly for patients at high recurrence risk. Notably, obesity profoundly affects the tumor microenvironment (TME) of LBC. However, it is unclear whether obesity-related biological features can effectively screen high-risk patients. Utilizing weighted gene coexpression network analysis (WGCNA) on RNA sequencing (RNAseq) data, we identified seven obese LBC genes (OLGs) closely associated with patient prognosis. Subsequently, we developed a luminal obesity-gene clinical prognostic index (LOG-CPI), combining a 7-gene signature, TNM staging, and age. Its predictive efficacy was confirmed across validation datasets and a clinical cohort (5-year accuracy = 0.828, 0.760, 0.751, and 0.792, respectively). LOG-CPI emerges as a promising predictor for clinical prognosis and treatment response, helping distinguish molecular and immunological features in LBC patients and guiding clinical practice by identifying varying prognoses.
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Affiliation(s)
- Hengjun Zhang
- Department of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, P.R. China
| | - Shuai Ma
- Department of Thyroid and Breast Surgery, People’s Hospital of China Medical University (Liaoning Provincial People's Hospital), Shenyang, China
| | - Yusong Wang
- Department of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, P.R. China
| | - Xiuyun Chen
- Department of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, P.R. China
| | - Yumeng Li
- Department of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, P.R. China
| | - Mozhi Wang
- Department of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, P.R. China
| | - Yingying Xu
- Department of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, P.R. China
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Wu Y, Zhang X, Chen Y, Chen W, Qian W. Identification the Low Oxidative Stress Subtype of Periodontitis. Int Dent J 2024; 74:119-128. [PMID: 37821327 PMCID: PMC10829343 DOI: 10.1016/j.identj.2023.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/07/2023] [Accepted: 07/20/2023] [Indexed: 10/13/2023] Open
Abstract
OBJECTIVE The aim of this research was to identify the low oxidative stress-related genes expression (L-OS) subtype in patients with periodontitis. METHODS Microarray data (MA) were retrieved from the Gene Expression Omnibus database. The different oxidative stress (OS) subtypes of periodontitis were identified by K-means clustering analysis and gene set variation analysis (GSVA). Differentially expressed genes (DEGs) (|Log fold change (FC)| >1, q < 0.05) amongst the OS subtypes and healthy controls (HCs) were identified by Limma R package. The genomic feature of L-OS subtype and corresponding medicines were evaluated and visualised with Drug-Gene Interaction Database and cytoscape-v3.7.2 software (Pearson correlation coefficient > 0.4). Finally, the LASSO-Logistic regression model was adopted to evaluate and predict patients' OS phenotype in routine clinical practice. RESULTS The 241 periodontitis samples and 69 HCs were included. Thirty-three DEGs between the L-OS and high oxidative stress-related genes expression (H-OS) subtypes and 96 DEGs, including 8 transcription factors, between L-OS subtype and HCs were identified, respectively. Then, the network of TFs-Genes-Drugs was constructed to determine genomic feature of L-OS subtype. Finally, a 4-gene signature formula and the cutoff value were identified by ML with LASSO model to predict patients' classification. CONCLUSIONS For the first time, we identified L-OS subtype of periodontitis and evaluated its genomic feature with MA.
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Affiliation(s)
- Yuchen Wu
- Department of Prosthodontics, Shanghai Xuhui District Dental Center, Shanghai, People's Republic of China
| | - Xianfang Zhang
- Department of Prosthodontics, Shanghai Xuhui District Dental Center, Shanghai, People's Republic of China
| | - Yunong Chen
- Department of Prosthodontics, Shanghai Xuhui District Dental Center, Shanghai, People's Republic of China
| | - Weiting Chen
- Department of Periodontology, Shanghai Xuhui District Dental Center, Shanghai, People's Republic of China
| | - Wenhao Qian
- Department of Oral Implantology, Shanghai Xuhui District Dental Center, Shanghai, People's Republic of China.
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Zhang Z, Zhao C, Yang S, Lu W, Shi J. A novel lipid metabolism-based risk model associated with immunosuppressive mechanisms in diffuse large B-cell lymphoma. Lipids Health Dis 2024; 23:20. [PMID: 38254162 PMCID: PMC10801940 DOI: 10.1186/s12944-024-02017-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 01/12/2024] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND The molecular diversity exhibited by diffuse large B-cell lymphoma (DLBCL) is a significant obstacle facing current precision therapies. However, scoring using the International Prognostic Index (IPI) is inadequate when fully predicting the development of DLBCL. Reprogramming lipid metabolism is crucial for DLBCL carcinogenesis and expansion, while a predictive approach derived from lipid metabolism-associated genes (LMAGs) has not yet been recognized for DLBCL. METHODS Gene expression profiles of DLBCL were generated using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The LASSO Cox regression was used to construct an effective predictive risk-scoring model for DLBCL patients. The Kaplan-Meier survival assessment was employed to compare a given risk score with the IPI score and its impact on the survival of DLBCL patients. Functional enrichment examination was performed utilizing the KEGG pathway. After identifying hub genes via single-sample GSEA (ssGSEA), immunohistochemical staining and immunofluorescence were performed on lymph node samples from control and DLBCL patients to confirm these identified genes. RESULTS Sixteen lipid metabolism- and survival-associated genes were identified to construct a prognostic risk-scoring approach. This model demonstrated robust performance over various datasets and emerged as an autonomous risk factor for predicting the development of DLBCL patients. The risk score could significantly distinguish the development of DLBCL patients from the low-risk and elevated-risk IPI classes. Results from the inhibitory immune-related pathways and lower immune scores suggested an immunosuppressive phenotype within the elevated-risk group. Three hub genes, MECR, ARSK, and RAN, were identified to be negatively correlated with activated CD8 T cells and natural killer T cells in the elevated-risk score class. Ultimately, it was determined that these three genes were expressed by lymphoma cells but not by T cells in clinical samples from DLBCL patients. CONCLUSION The risk level model derived from 16 lipid metabolism-associated genes represents a prognostic biomarker for DLBCL that is novel, robust, and may have an immunosuppressive role. It can compensate for the limitations of the IPI score in predicting overall survival and has potential clinical application value.
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Affiliation(s)
- Zhaoli Zhang
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Chong Zhao
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shaoxin Yang
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wei Lu
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
| | - Jun Shi
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
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Mulati Y, Lai C, Luo J, Hu J, Xu X, Kong D, Xiao Y, Liu C, Xu K. Establishment of a prognostic risk prediction model incorporating disulfidptosis-related lncRNA for patients with prostate cancer. BMC Cancer 2024; 24:44. [PMID: 38191330 PMCID: PMC10775669 DOI: 10.1186/s12885-023-11778-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 12/20/2023] [Indexed: 01/10/2024] Open
Abstract
PURPOSE Prostate cancer (PCa) is one of the major tumor diseases that threaten men's health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two. METHODS Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted. RESULTS The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue. CONCLUSIONS A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.
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Affiliation(s)
- Yelisudan Mulati
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510000, Guangzhou, Guangdong, China
| | - Cong Lai
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510000, Guangzhou, Guangdong, China
| | - Jiawen Luo
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510000, Guangzhou, Guangdong, China
| | - Jintao Hu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510000, Guangzhou, Guangdong, China
| | - Xiaoting Xu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510000, Guangzhou, Guangdong, China
| | - Degeng Kong
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510000, Guangzhou, Guangdong, China
| | - Yunfei Xiao
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510000, Guangzhou, Guangdong, China
| | - Cheng Liu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, 510000, Guangzhou, Guangdong, China
| | - Kewei Xu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, 510000, Guangzhou, Guangdong, China.
- Guangdong Provincial Clinical Research Center for Urological Diseases, 510000, Guangzhou, Guangdong, China.
- Sun Yat-sen University School of Medicine, Sun Yat-sen University, 518000, Shenzhen, Guangdong, China.
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Zhang S, Ji B, Li J, Ji W, Yang C, Yang L. FBXL5 promotes lipid accumulation in alcoholic fatty liver disease by promoting the ubiquitination and degradation of TFEB. Cell Signal 2023; 112:110905. [PMID: 37743009 DOI: 10.1016/j.cellsig.2023.110905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 09/09/2023] [Accepted: 09/22/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Alcoholic fatty liver disease (AFLD) is characterized by abnormal lipid droplet accumulation in liver. Epigenetic regulation plays an important role in the pathogenesis of AFLD. Comprehensive bioinformatics analysis revealed that an E3 ubiquitin ligase, F-box and leucine-rich repeats protein 5 (FBXL5), was significantly upregulated in AFLD mice. METHODS The mouse model of AFLD was established by feeding Lieber-DeCarli liquid diet containing ethanol. An in vitro model of AFLD was established by treating HepG2 cells with ethanol (EtOH). The FBXL5 expression was assessed by quantitative real-time PCR (qRT-PCR) and western blotting assays. The levels of triglyceride (TG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lipid accumulation were analyzed by enzyme-linked immunosorbent assay (ELISA) and Nile red staining. RESULTS The FBXL5 expression was markedly up-regulated in in vivo and in vitro models of AFLD compared with controls. Functionally, FBXL5 knockdown alleviated lipid accumulation in EtOH-treated HepG2 cells. Mechanistically, FBXL5 directly interacted with transcription factor EB (TFEB) and accelerated its ubiquitination-mediated degradation. TFEB knockdown reversed the effect of FBXL5 inhibition on decreasing EtOH-induced lipid accumulation. CONCLUSION Our data suggest that FBXL5 promotes lipid accumulation in AFLD by promoting the ubiquitination and degradation of TFEB.
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Affiliation(s)
- Shuo Zhang
- Department of Gastroenterology and Hepatology, School of Medicine, Shanghai Tongji Hospital, Tongji University, Shanghai 200092, China
| | - Bing Ji
- Department of Gastroenterology and Hepatology, School of Medicine, Shanghai Tongji Hospital, Tongji University, Shanghai 200092, China
| | - Jing Li
- Department of Gastroenterology and Hepatology, School of Medicine, Shanghai Tongji Hospital, Tongji University, Shanghai 200092, China
| | - Wenjing Ji
- Department of Gastroenterology, Second Affiliated Hospital of Xinjiang Medical University, Ürümqi, China
| | - Changqing Yang
- Department of Gastroenterology and Hepatology, School of Medicine, Shanghai Tongji Hospital, Tongji University, Shanghai 200092, China.
| | - Li Yang
- Department of Gastroenterology and Hepatology, School of Medicine, Shanghai Tongji Hospital, Tongji University, Shanghai 200092, China; Department of Gastroenterology, Second Affiliated Hospital of Xinjiang Medical University, Ürümqi, China.
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Wang X, Zhou L, Wang H, Chen W, Jiang L, Ming G, Wang J. Metabolic reprogramming, autophagy, and ferroptosis: Novel arsenals to overcome immunotherapy resistance in gastrointestinal cancer. Cancer Med 2023; 12:20573-20589. [PMID: 37860928 PMCID: PMC10660574 DOI: 10.1002/cam4.6623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/05/2023] [Accepted: 09/29/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Gastrointestinal cancer poses a serious health threat owing to its high morbidity and mortality. Although immune checkpoint blockade (ICB) therapies have achieved meaningful success in most solid tumors, the improvement in survival in gastrointestinal cancers is modest, owing to sparse immune response and widespread resistance. Metabolic reprogramming, autophagy, and ferroptosis are key regulators of tumor progression. METHODS A literature review was conducted to investigate the role of the metabolic reprogramming, autophagy, and ferroptosis in immunotherapy resistance of gastrointestinal cancer. RESULTS Metabolic reprogramming, autophagy, and ferroptosis play pivotal roles in regulating the survival, differentiation, and function of immune cells within the tumor microenvironment. These processes redefine the nutrient allocation blueprint between cancer cells and immune cells, facilitating tumor immune evasion, which critically impacts the therapeutic efficacy of immunotherapy for gastrointestinal cancers. Additionally, there exists profound crosstalk among metabolic reprogramming, autophagy, and ferroptosis. These interactions are paramount in anti-tumor immunity, further promoting the formation of an immunosuppressive microenvironment and resistance to immunotherapy. CONCLUSIONS Consequently, it is imperative to conduct comprehensive research on the roles of metabolic reprogramming, autophagy, and ferroptosis in the resistance of gastrointestinal tumor immunotherapy. This understanding will illuminate the clinical potential of targeting these pathways and their regulatory mechanisms to overcome immunotherapy resistance in gastrointestinal cancers.
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Affiliation(s)
- Xiangwen Wang
- Department of General SurgeryThe First Hospital of Lanzhou UniversityLanzhouChina
| | - Liwen Zhou
- Department of StomatologyThe First Hospital of Lanzhou UniversityLanzhouChina
| | - Hongpeng Wang
- Department of General SurgeryThe First Hospital of Lanzhou UniversityLanzhouChina
| | - Wei Chen
- Department of General SurgeryThe First Hospital of Lanzhou UniversityLanzhouChina
| | - Lei Jiang
- Department of General SurgeryThe First Hospital of Lanzhou UniversityLanzhouChina
| | - Guangtao Ming
- Department of General SurgeryThe First Hospital of Lanzhou UniversityLanzhouChina
| | - Jun Wang
- Department of General SurgeryThe First Hospital of Lanzhou UniversityLanzhouChina
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Liu T, Wei J. The potential bioactive ingredients and hub genes of five TCM prescriptions against lung adenocarcinoma were explored based on bioinformatics. NAUNYN-SCHMIEDEBERG'S ARCHIVES OF PHARMACOLOGY 2023; 396:2039-2055. [PMID: 36914901 DOI: 10.1007/s00210-023-02430-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 02/16/2023] [Indexed: 03/15/2023]
Abstract
Analysis of the commonness of several prescriptions of traditional Chinese medicine (TCM) in the treatment of lung adenocarcinoma (LUAD) based on bioinformatics. Searched the TCM prescriptions for the treatment of LUAD in the literature published in the database, searched ingredients in the TCM through TCMSP and Swiss target prediction databases (OB ≥ 30%, DL > 0.18, Caco-2 > 0), and predicted the potential targets. GEO database retrieved LUAD gene chip data and screened (P < 0.05, | log2 (fold change) |> 1). The biological function, hub gene selection and survival period, immune infiltration, methylation, copy number variations (CNVs), and single-nucleotide variants (SNV) of hub genes were analyzed by DAVID, STRING, Kaplan-Meier plotter database, Cytoscape software, GSCALite database, and TIMER2.0. In this study, 5 TCM prescriptions were analyzed, and a total of 173 ingredients were obtained through database search, including 35 coincidence ingredients, a total of 603 potential targets, 621 LUAD-related genes, 16 up-regulated genes, and 31 down-regulated genes. A total of 61 terms of biological process (BP), 14 terms of cellular component (CC), and 14 terms of molecular function (MF) were obtained. Twenty core genes were obtained, including 15 genes with different survival periods, which were closely related to immune cells (B cell, CD8 + T cell, CD4 + T cell, macrophage, neutrophil, and dendritic cells). The low expression of ADRB2 and MAOA and the high expression of AUARK, CDK1, KIF11, MIF, TOP2A, and TTK were associated with the survival rate of LUAD patients (P < 0.05). Baicalein, Arachidonate, Hederagenin, and hub genes may become potential drugs and potential targets for LUAD treatment. Evaluated the efficacy of TCM in the treatment of LUAD from macro to micro, mined the hub genes, and predicted the mechanism of action, so as to lay the foundation for the development of new drugs of TCM, prescription optimization, or disease control.
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Affiliation(s)
- Tingting Liu
- Institute for Brain Sciences Research, School of Life Sciences, Henan University, Kaifeng, 475004, People's Republic of China
| | - Jianshe Wei
- Institute for Brain Sciences Research, School of Life Sciences, Henan University, Kaifeng, 475004, People's Republic of China.
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Xu X, Zhang X, Lin Q, Qin Y, Liu Y, Tang W. Integrated single-cell and bulk RNA sequencing analysis identifies a prognostic signature related to ferroptosis dependence in colorectal cancer. Sci Rep 2023; 13:12653. [PMID: 37542061 PMCID: PMC10403602 DOI: 10.1038/s41598-023-39412-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 07/25/2023] [Indexed: 08/06/2023] Open
Abstract
Ferroptosis is an iron-dependent form of cell death induced by lipid oxidation with an essential role in diseases, including cancer. Since prognostic value of ferroptosis-dependent related genes (FDRGs) in colorectal cancer (CRC) remains unclear, we explored the significance of FDRGs in CRC through comprehensive single-cell analysis. We downloaded the GSE161277 dataset for single-cell analyses and calculated the ferroptosis-dependent gene score (FerrScore) for each cell type. According to each cell type-specific median FerrScore, we categorized the cells into low- and high-ferroptosis groups. By analyzing differentially-expressed genes across the two groups, we identified FDRGs. We further screened these prognosis-related genes used to develop a prognostic signature and calculated its correlation with immune infiltration. We also compared immune checkpoint gene efficacy among different risk groups, and qRT-PCR was performed in colorectal normal and cancer cell lines to explore whether the signature genes could be used as clinical prognostic indicators. In total, 523 FDRGs were identified. A prognostic signature including five signature genes was constructed, and patients were divided into two risk groups. The high-risk group had poor survival rates and displayed high levels of immune infiltration. Our newly developed ferroptosis-based prognostic signature possessed a high predictive ability for CRC.
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Affiliation(s)
- Xiaochen Xu
- Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, 530021, Guangxi Zhuang Autonomous Region, China
| | - Xinwen Zhang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Guilin Medical University, Guilin, 541001, Guangxi Zhuang Autonomous Region, China
| | - Qiumei Lin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, 530021, Guangxi Zhuang Autonomous Region, China
| | - Yuling Qin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, 530021, Guangxi Zhuang Autonomous Region, China
| | - Yihao Liu
- Department of Gastrointestinal Surgery, Affiliated Hospital of Guilin Medical University, Guilin, 541001, Guangxi Zhuang Autonomous Region, China
| | - Weizhong Tang
- Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, 530021, Guangxi Zhuang Autonomous Region, China.
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Jiang Q, Zhou J, Chen Q, Huang Y, Yang C, Liu C. Construction and experimental validation of a macrophage cell senescence-related gene signature to evaluate the prognosis, immunotherapeutic sensitivity, and chemotherapy response in bladder cancer. Funct Integr Genomics 2023; 23:228. [PMID: 37423913 DOI: 10.1007/s10142-023-01163-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/28/2023] [Accepted: 06/29/2023] [Indexed: 07/11/2023]
Abstract
Tumor-associated macrophages (TAMs) are pivotal components of tumor microenvironment (TME), and senescent TAMs contribute to the alternation of the profiles of TME. However, the potential biological mechanisms and the prognosis value of senescent macrophages are largely unknown, especially in bladder cancer (BLCA). Based on the single-cell RNA sequencing of a primary BLCA sample, 23 macrophage-related genes were identified. Genomic difference analysis, LASSO, and Cox regression were used to develop the risk model. TCGA-BLCA cohort (n = 406) was utilized as the training cohort, and then, three independent cohorts (n = 90, n = 221, n = 165) from Gene Expression Omnibus, clinical samples from the local hospital (n = 27), and in vitro cell experiments were used for external validation. Aldo-keto reductase family 1 member B (AKR1B1), inhibitor of DNA binding 1 (ID1), and transforming growth factor beta 1 (TGFB1I1) were determined and included in the predictive model. The model serves as a promising tool to evaluate the prognosis in BLCA (pooled hazard ratio = 2.51, 95% confidence interval = [1.43; 4.39]). The model was also effective for the prediction of immunotherapeutic sensitivity and chemotherapy treatment outcomes, which were further confirmed by IMvigor210 cohort (P < 0.01) and GDSC dataset, respectively. Twenty-seven BLCA samples from the local hospital proved that the risk model was associated with the malignant degree (P < 0.05). At last, the human macrophage THP-1 and U937 cells were treated with H2O2 to mimic the senescent process in macrophage, and the expressions of these molecules in the model were detected (all P < 0.05).Overall, a macrophage cell senescence-related gene signature was constructed to predict the prognosis, immunotherapeutic response, and chemotherapy sensitivity in BLCA, which provides novel insights to uncover the underlying mechanisms of macrophage senescence.
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Affiliation(s)
- Qijun Jiang
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China
| | - Junhao Zhou
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China
| | - Qi Chen
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China
| | - Yuliang Huang
- Department of Nephrology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China
| | - Cheng Yang
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China
| | - Cundong Liu
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China.
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Wang L, Bao Y, Yu F, Zhu W, Wang JL, Yang J, Xie H, Huang D. Development of gene model combined with machine learning technology to predict for advanced atherosclerotic plaques. Clin Neurol Neurosurg 2023; 231:107819. [PMID: 37315377 DOI: 10.1016/j.clineuro.2023.107819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 05/03/2023] [Accepted: 06/04/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND Atherosclerosis, as a major cause of stroke, is responsible for a quarter of deaths worldwide. In particular, rupture of late-stage plaques in large vessels such as the carotid artery can lead to serious cardiovascular disease. The aim of our study was to establish a genetic model combined with machining leaning techniques to screen out gene signatures and predict for advanced atherosclerosis plaques. METHODS The microarray dataset GSE28829 and GSE43292 which were publicly obtained from the Gene Expression Omnibus database were utilized to screen for potential predictive genes. Differentially expressed genes (DEGs) were identified by using the "limma" R package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes Genomes (KEGG) analyses of these DEGs were performed by Metascape. Later, Random Forest (RF) algorithm was applied to further screen out top-30 genes which contribute the most. The expression data of top 30-DEGs were converted into a "Gene Score". Finally, we developed a model based on artificial neural network (ANN) to predict advanced atherosclerotic plaques. The model later was validated in an independent test dataset GSE104140. RESULTS A total of 176 DEGs were identified in the training datasets. GO and KEGG enrichment analysis revealed that these genes were enriched in leukocyte-mediated immune response, cytokine- cytokine interactions, and immunoinflammatory signaling. Further, top-30 genes (including 25 upregulated and 5 downregulated DEGs) were screened as predictors by RF algorithm. The predictive model was developed with a significantly predictive value (AUC = 0.913) in the training datasets, and was validated with an independent dataset GSE104140 (AUC = 0.827). CONCLUSION In present study, our prediction model was established and showed satisfactory predictive power in both training and test datasets. In addition, this is the first study adopted bioinformatics methods combined with machine learning techniques (RF and ANN) to explore and predict for the advanced atherosclerotic plaques. However, further investigations were needed to verify the screened DEGs and predictive effectiveness of this model.
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Affiliation(s)
- Lufeng Wang
- Department of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yiwen Bao
- Department of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Fei Yu
- Department of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Wenxia Zhu
- Department of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jun Lang Wang
- Department of Imaging, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Yang
- Department of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Hongrong Xie
- Department of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
| | - Dongya Huang
- Department of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
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Liu L, Mo M, Chen X, Chao D, Zhang Y, Chen X, Wang Y, Zhang N, He N, Yuan X, Chen H, Yang J. Targeting inhibition of prognosis-related lipid metabolism genes including CYP19A1 enhances immunotherapeutic response in colon cancer. J Exp Clin Cancer Res 2023; 42:85. [PMID: 37055842 PMCID: PMC10100168 DOI: 10.1186/s13046-023-02647-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 03/14/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Lipid metabolic reprogramming in colon cancer shows a potential impact on tumor immune microenvironment and is associated with response to immunotherapy. Therefore, this study aimed to develop a lipid metabolism-related prognostic risk score (LMrisk) to provide new biomarkers and combination therapy strategies for colon cancer immunotherapy. METHODS Differentially expressed lipid metabolism-related genes (LMGs) including cytochrome P450 (CYP) 19A1 were screened to construct LMrisk in TCGA colon cancer cohort. The LMrisk was then validated in three GEO datasets. The differences of immune cell infiltration and immunotherapy response between LMrisk subgroups were investigated via bioinformatic analysis. These results were comfirmed by in vitro coculture of colon cancer cells with peripheral blood mononuclear cells, human colon cancer tissue microarray analysis, multiplex immunofluorescence staining and mouse xenograft models of colon cancer. RESULTS Six LMGs including CYP19A1, ALOXE3, FABP4, LRP2, SLCO1A2 and PPARGC1A were selected to establish the LMrisk. The LMrisk was positively correlated with the abundance of macrophages, carcinoma-associated fibroblasts (CAFs), endothelial cells and the levels of biomarkers for immunotherapeutic response including programmed cell death ligand 1 (PD-L1) expression, tumor mutation burden and microsatellite instability, but negatively correlated with CD8+ T cell infiltration levels. CYP19A1 protein expression was an independent prognostic factor, and positively correlated with PD-L1 expression in human colon cancer tissues. Multiplex immunofluorescence analyses revealed that CYP19A1 protein expression was negatively correlated with CD8+ T cell infiltration, but positively correlated with the levels of tumor-associated macrophages, CAFs and endothelial cells. Importantly, CYP19A1 inhibition downregulated PD-L1, IL-6 and TGF-β levels through GPR30-AKT signaling, thereby enhancing CD8+ T cell-mediated antitumor immune response in vitro co-culture studies. CYP19A1 inhibition by letrozole or siRNA strengthened the anti-tumor immune response of CD8+ T cells, induced normalization of tumor blood vessels, and enhanced the efficacy of anti-PD-1 therapy in orthotopic and subcutaneous mouse colon cancer models. CONCLUSION A risk model based on lipid metabolism-related genes may predict prognosis and immunotherapeutic response in colon cancer. CYP19A1-catalyzed estrogen biosynthesis promotes vascular abnormality and inhibits CD8+ T cell function through the upregulation of PD-L1, IL-6 and TGF-β via GPR30-AKT signaling. CYP19A1 inhibition combined with PD-1 blockade represents a promising therapeutic strategy for colon cancer immunotherapy.
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Affiliation(s)
- Lilong Liu
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Min Mo
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Xuehan Chen
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Dongchen Chao
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Yufan Zhang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Xuewei Chen
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Yang Wang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Nan Zhang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Nan He
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Xi Yuan
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Honglei Chen
- Department of Pathology, School of Basic Medical Sciences, Wuhan University, Wuhan, 430071, China.
| | - Jing Yang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China.
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Xiong Z, Li W, Luo X, Lin Y, Huang W, Zhang S. Seven bacterial response-related genes are biomarkers for colon cancer. BMC Bioinformatics 2023; 24:103. [PMID: 36941538 PMCID: PMC10026208 DOI: 10.1186/s12859-023-05204-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 02/23/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Colon cancer (CC) is a common tumor that causes significant harm to human health. Bacteria play a vital role in cancer biology, particularly the biology of CC. Genes related to bacterial response were seldom used to construct prognosis models. We constructed a bacterial response-related risk model based on three Molecular Signatures Database gene sets to explore new markers for predicting CC prognosis. METHODS The Cancer Genome Atlas (TCGA) colon adenocarcinoma samples were used as the training set, and Gene Expression Omnibus (GEO) databases were used as the test set. Differentially expressed bacterial response-related genes were identified for prognostic gene selection. Univariate Cox regression analysis, least absolute shrinkage and selection operator-penalized Cox regression analysis, and multivariate Cox regression analysis were performed to construct a prognostic risk model. The individual diagnostic effects of genes in the prognostic model were also evaluated. Moreover, differentially expressed long noncoding RNAs (lncRNAs) were identified. Finally, the expression of these genes was validated using quantitative polymerase chain reaction (qPCR) in cell lines and tissues. RESULTS A prognostic signature was constructed based on seven bacterial response genes: LGALS4, RORC, DDIT3, NSUN5, RBCK1, RGL2, and SERPINE1. Patients were assigned a risk score based on the prognostic model, and patients in the TCGA cohort with a high risk score had a poorer prognosis than those with a low risk score; a similar finding was observed in the GEO cohort. These seven prognostic model genes were also independent diagnostic factors. Finally, qPCR validated the differential expression of the seven model genes and two coexpressed lncRNAs (C6orf223 and SLC12A9-AS1) in 27 pairs of CC and normal tissues. Differential expression of LGALS4 and NSUN5 was also verified in cell lines (FHC, COLO320DM, SW480). CONCLUSIONS We created a seven-gene bacterial response-related gene signature that can accurately predict the outcomes of patients with CC. This model can provide valuable insights for personalized treatment.
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Affiliation(s)
- Zuming Xiong
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Wenxin Li
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Xiangrong Luo
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Yirong Lin
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Wei Huang
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Sen Zhang
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
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Peng S, Fu Y. FYN: emerging biological roles and potential therapeutic targets in cancer. J Transl Med 2023; 21:84. [PMID: 36740671 PMCID: PMC9901160 DOI: 10.1186/s12967-023-03930-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 01/25/2023] [Indexed: 02/07/2023] Open
Abstract
Src family protein kinases (SFKs) play a key role in cell adhesion, invasion, proliferation, survival, apoptosis, and angiogenesis during tumor development. In humans, SFKs consists of eight family members with similar structure and function. There is a high level of overexpression or hyperactivity of SFKs in tumor, and they play an important role in multiple signaling pathways involved in tumorigenesis. FYN is a member of the SFKs that regulate normal cellular processes. Additionally, FYN is highly expressed in many cancers and promotes cancer growth and metastasis through diverse biological functions such as cell growth, apoptosis, and motility migration, as well as the development of drug resistance in many tumors. Moreover, FYN is involved in the regulation of multiple cancer-related signaling pathways, including interactions with ERK, COX-2, STAT5, MET and AKT. FYN is therefore an attractive therapeutic target for various tumor types, and suppressing FYN can improve the prognosis and prolong the life of patients. The purpose of this review is to provide an overview of FYN's structure, expression, upstream regulators, downstream substrate molecules, and biological functions in tumors.
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Affiliation(s)
- SanFei Peng
- grid.412633.10000 0004 1799 0733Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 China
| | - Yang Fu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
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Effects of Lipid Metabolism-Related Genes PTGIS and HRASLS on Phenotype, Prognosis, and Tumor Immunity in Lung Squamous Cell Carcinoma. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2023; 2023:6811625. [PMID: 36703911 PMCID: PMC9873467 DOI: 10.1155/2023/6811625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 12/21/2022] [Accepted: 01/02/2023] [Indexed: 01/19/2023]
Abstract
Background Lipid metabolism reprogramming played an important role in cancer occurrence, development, and immune regulation. The aim of this study was to identify and validate lipid metabolism-related genes (LMRGs) associated with the phenotype, prognosis, and immunological characteristics of lung squamous cell carcinoma (LUSC). Methods In the TCGA cohort, bioinformatics and survival analysis were used to identify lipid metabolism-related differentially expressed genes (DEGs) associated with the prognosis of LUSC. PTGIS/HRASLS knockdown and overexpression effects on the LUSC phenotype were analyzed in vitro experiments. Based on the expression distribution of PTGIS/HRASLS, LUSC patients were divided into two clusters by consensus clustering. Clinical information, prognosis, immune infiltration, expression of immune checkpoints, and tumor mutation burden (TMB) level were compared between the TCGA and GSE4573 cohorts. The genes related to clustering and tumor immunity were screened by weighted gene coexpression network analysis (WGCNA), and the target module genes were analyzed by functional enrichment analysis, protein-protein interaction (PPI) analysis, and immune correlation analysis. Results 191 lipid metabolism-related DEGs were identified, of which 5 genes were independent prognostic genes of LUSC. PTGIS/HRASLS were most closely related to LUSC prognosis and immunity. RT-qPCR, western blot (WB) analysis, and immunohistochemistry (IHC) showed that the expression of PTGIS was low in LUSC, while HRASLS was high. Functionally, PTGIS promoted LUSC proliferation, migration, and invasion, while HRASLS inhibited LUSC proliferation, migration, and invasion. The two clusters' expression and distribution of PTGIS/HRASLS had the opposite trend. Cluster 1 was associated with lower pathological staging (pT, pN, and pTNM stages), better prognosis, stronger immune infiltration, higher expression of immune checkpoints, and higher TMB level than cluster 2. WGCNA found that 28 genes including CD4 and IL10RA were related to the expression of PTGIS/HRASLS and tumor immune infiltration. PTGIS/HRASLS in the GSE4573 cohort had the same effect on LUSC prognosis and tumor immunity as the TCGA cohort. Conclusions PTGIS and HRASLS can be used as new therapeutic targets for LUSC as well as biomarkers for prognosis and tumor immunity, which has positive significance for guiding the immunotherapy of LUSC.
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Miao Y, Yuan Q, Wang C, Feng X, Ren J, Wang C. Comprehensive Characterization of RNA-Binding Proteins in Colon Adenocarcinoma Identifies a Novel Prognostic Signature for Predicting Clinical Outcomes and Immunotherapy Responses Based on Machine Learning. Comb Chem High Throughput Screen 2023; 26:163-182. [PMID: 35379120 DOI: 10.2174/1386207325666220404125228] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND RNA-binding proteins (RBPs) are crucial factors that function in the posttranscriptional modification process and are significant in cancer. OBJECTIVE This research aimed for a multigene signature to predict the prognosis and immunotherapy response of patients with colon adenocarcinoma (COAD) based on the expression profile of RNA-binding proteins (RBPs). METHODS COAD samples retrieved from the TCGA and GEO datasets were utilized for a training dataset and a validation dataset. Totally, 14 shared RBP genes with prognostic significance were identified. Non-negative matrix factorization clusters defined by these RBPs could stratify COAD patients into two molecular subtypes. Cox regression analysis and identification of 8-gene signature categorized COAD patients into high- and low-risk populations with significantly different prognosis and immunotherapy responses. RESULTS Our prediction signature was superior to another five well-established prediction models. A nomogram was generated to quantificationally predict the overall survival (OS) rate, validated by calibration curves. Our findings also indicated that high-risk populations possessed an enhanced immune evasion capacity and low-risk populations might benefit immunotherapy, especially for the joint combination of PD-1 and CTLA4 immunosuppressants. DHX15 and LARS2 were detected with significantly different expressions in both datasets, which were further confirmed by qRTPCR and immunohistochemical staining. CONCLUSION Our observations supported an eight-RBP-related signature that could be applied for survival prediction and immunotherapy response of patients with COAD.
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Affiliation(s)
- Ye Miao
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Department of Neurosurgery, First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Qihang Yuan
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Chao Wang
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Xiaoshi Feng
- Department of Endocrinology, First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China
| | - Jie Ren
- Department of Oncology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Changmiao Wang
- Department of Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
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Chen Y, Lu Y, Huang C, Wu J, Shao Y, Wang Z, Zhang H, Fu Z. Subtypes analysis and prognostic model construction based on lysosome-related genes in colon adenocarcinoma. Front Genet 2023; 14:1149995. [PMID: 37168510 PMCID: PMC10166181 DOI: 10.3389/fgene.2023.1149995] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/12/2023] [Indexed: 05/13/2023] Open
Abstract
Background: Lysosomes are essential for the development and recurrence of cancer. The relationship between a single lysosome-related gene and cancer has previously been studied, but the relationship between the lysosome-related genes (LRGs) and colon adenocarcinoma (COAD) remains unknown. This research examined the role of lysosome-related genes in colon adenocarcinoma. Methods: 28 lysosome-related genes associated with prognosis (PLRGs) were found by fusing the gene set that is differently expressed between tumor and non-tumor in colon adenocarcinoma with the gene set that is related to lysosomes. Using consensus unsupervised clustering of PLRGs, the colon adenocarcinoma cohort was divided into two subtypes. Prognostic and tumor microenvironment (TME) comparisons between the two subtypes were then made. The PLRGs_score was constructed using the least absolute shrinkage and selection operator regression (LASSO) method to quantify each patient's prognosis and provide advice for treatment. Lastly, Western Blot and immunohistochemistry (IHC) were used to identify MOGS expression at the protein level in colon adenocarcinoma tissues. Results: PLRGs had more somatic mutations and changes in genetic level, and the outcomes of the two subtypes differed significantly in terms of prognosis, tumor microenvironment, and enrichment pathways. Then, PLRGs_score was established based on two clusters of differential genes in the cancer genome atlas (TCGA) database, and external verification was performed using the gene expression omnibus (GEO) database. Then, we developed a highly accurate nomogram to enhance the clinical applicability of the PLRGs_score. Finally, a higher PLRGs_score was associated with a poorer overall survival (OS), a lower tumor mutation burden (TMB), a lower cancer stem cell (CSC) index, more microsatellite stability (MSS), and a higher clinical stage. MOGS was substantially elevated at the protein level in colon adenocarcinoma as additional confirmation. Conclusion: Overall, based on PLRGs, we identified two subtypes that varied significantly in terms of prognosis and tumor microenvironment. Then, in order to forecast patient prognosis and make treatment suggestions, we developed a diagnostic model with major significance for prognosis, clinical relevance, and immunotherapy. Moreover, we were the first to demonstrate that MOGS is highly expressed in colon adenocarcinoma.
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Affiliation(s)
- Yang Chen
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yunfei Lu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Changzhi Huang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jingyu Wu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yu Shao
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhenling Wang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongqiang Zhang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zan Fu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- The First College of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
- *Correspondence: Zan Fu,
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GDPD5 Related to Lipid Metabolism Is a Potential Prognostic Biomarker in Neuroblastoma. Int J Mol Sci 2022; 23:ijms232213740. [PMID: 36430219 PMCID: PMC9695425 DOI: 10.3390/ijms232213740] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 11/11/2022] Open
Abstract
Neuroblastoma (NB) is an extracranial solid tumor in children with poor prognosis in high-risk patients and its pathogenesis and prognostic markers urgently need to be explored. This study aimed to explore potential biomarkers related to NB from the aspect of lipid metabolism. Fifty-eight lipid metabolism-related differentially expressed genes between high-risk NB and non-high-risk NB in the GSE49710 dataset were analyzed using bioinformatics, including 45 down-regulated genes and 13 up-regulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified steroid hormone biosynthesis as an abnormal metabolic pathway in high-risk NB. Survival analysis established a three-gene prognostic model, including ACHE, GDPD5 and PIK3R1. In the test data, the AUCs of the established prognostic models used to predict patient survival at 1, 3 and 5 years were 0.84, 0.90 and 0.91, respectively. Finally, in the SH-SY5Y cell line, it was verified that overexpression of GDPD5 can inhibit cell proliferation and migration, as well as affect the lipid metabolism of SH-SY5Y, but not the sugar metabolism. hsa-miR-592 was predicted to be a potential target miRNA of GDPD5 by bioinformatics. In conclusion, this study develops a lipid-metabolism-related gene-based prognostic model for NB and demonstrates that GDPD5 inhibits SH-SY5Y proliferation and migration and may be targeted by hsa-miR-592 and inhibit SH-SY5Y fat synthesis.
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Xie Y, Chen H, Fang JY. Amino acid metabolism-based molecular classification of colon adenocarcinomavia in silico analysis. Front Immunol 2022; 13:1018334. [DOI: 10.3389/fimmu.2022.1018334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 10/03/2022] [Indexed: 11/13/2022] Open
Abstract
Amino acid metabolism is closely related to the occurrence and development of colon adenocarcinoma (COAD). Studies on the relationship between COAD and the expression of amino acid metabolism are still rare. Based on in silico analysis, we used 358 amino acid metabolism-related genes (AAMRGs) to determine the amino acid metabolism characteristics and then classified COAD into two distinct subtypes, namely AA1 and AA2. Then we analyzed the clinical characteristics, somatic mutation landscape, transcriptome profile, metabolism signatures, immune infiltration, and therapy sensitivity of these two subtypes. The AA1 subtype had inferior overall survival and was characterized by lower amino acid metabolic activity, higher tumor mutation burden, and higher immune cell infiltration, while AA2 displayed higher metabolic activity and relatively better survival. Furthermore, the AA1 subtype was likely to benefit from irinotecan in chemotherapy and immune checkpoint blockade therapy including programmed cell death protein-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) immune checkpoint inhibitor but was resistant to targeted therapy cetuximab. The AA2 subtype showed higher sensitivity to 5-fluorouracil and oxaliplatin. To provide perspectives on cell-specific metabolism for further investigation, we explored metabolic activity in different cell types including lymphocytes, mast cells, myeloid cells stromal cells, and epithelial cells via colorectal cancer single-cell data. Additionally, to assist in clinical decision-making and prognosis prediction, a 60-AAMRG-based classifier was generated and validated in an independent cohort.
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Zhang Z, Zhang Y, Yang D, Luo Y, Luo Y, Ru Y, Song J, Fei X, Chen Y, Li B, Jiang J, Kuai L. Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics. Int Wound J 2022; 20:529-542. [PMID: 36181454 PMCID: PMC9885479 DOI: 10.1111/iwj.13900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 07/02/2022] [Accepted: 07/04/2022] [Indexed: 02/03/2023] Open
Abstract
Diabetic ulcers (DUs) are characterised by a high incidence and disability rate. However, its pathogenesis remains elusive. Thus, a deep understanding of the underlying mechanisms for the pathogenesis of DUs has vital implications. The weighted gene co-expression network analysis was performed on the main data from the Gene Expression Omnibus database. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were adopted to analyse the potential biological function of the most relevant module. Furthermore, we utilised CytoHubba and protein-protein interaction network to identify the hub genes. Finally, the hub genes were validated by animal experiments in diabetic ulcer mice models. The expression of genes from the turquoise module was found to be strongly related to DUs. GO terms, KEGG analysis showed that biological functions are closely related to immune response. The hub genes included IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1, which were higher in wounds of DUs mice than that in normal lesions. Additionally, we also demonstrated that the expression of hub genes was correlated with the immune response using immune checkpoint, immune cell infiltration, and immune scores. These data suggests that IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1 are crucial for DUs.
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Affiliation(s)
- Zhan Zhang
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina,Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina
| | - Ying Zhang
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina,Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina
| | - Dan Yang
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina,Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina
| | - Yue Luo
- Department of Integrated TCM and Western Medicine, Shanghai Skin Disease HospitalTongji UniversityShanghaiChina
| | - Ying Luo
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina,Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina
| | - Yi Ru
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina,Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina
| | - Jiankun Song
- Department of Integrated TCM and Western Medicine, Shanghai Skin Disease HospitalTongji UniversityShanghaiChina
| | - Xiaoya Fei
- Department of Integrated TCM and Western Medicine, Shanghai Skin Disease HospitalTongji UniversityShanghaiChina
| | - Yiran Chen
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina,Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina
| | - Bin Li
- Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina,Department of Integrated TCM and Western Medicine, Shanghai Skin Disease HospitalTongji UniversityShanghaiChina
| | - Jingsi Jiang
- Department of Skin and Cosmetics Research, Shanghai Skin Disease HospitalTongji UniversityShanghaiChina
| | - Le Kuai
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina,Institute of DermatologyShanghai Academy of Traditional Chinese MedicineShanghaiChina
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Construction and Validation of Pyroptosis-Related lncRNA Prediction Model for Colon Adenocarcinoma and Immune Infiltration Analysis. DISEASE MARKERS 2022; 2022:4492608. [PMID: 36168326 PMCID: PMC9509522 DOI: 10.1155/2022/4492608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/26/2022] [Accepted: 09/01/2022] [Indexed: 11/26/2022]
Abstract
Objective Colon adenocarcinoma (COAD) is one of the most prevalent cancers worldwide. However, the pyroptosis-related lncRNAs of COAD have not been deeply examined and validated. Here, we constructed and validated a risk model on pyroptosis-related lncRNAs in COAD. Methods The RNA sequencing transcriptome and clinical data of COAD patients were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed pyroptosis-related mRNAs and mRNA-lncRNA coexpression network were identified. After univariate and multifactorial cox analyses of prognosis-related lncRNAs, a risk model was constructed. Next, we analyzed the differences in immune infiltration, immune checkpoint blockade-, immune checkpoint-, and N6-methyladenosine-related gene expressions between the high- and low-risk groups. RT-qPCR was used to validate the expression of lncRNAs. Result A risk model was constructed based on 9 pyroptosis-related lncRNAs and separated COAD patients into the high- and low-risk groups. Immune infiltration analysis and immune checkpoint blockade-, immune checkpoint-, and N6-methyladenosine-related genes showed significant differences between the two subgroups. RT-qPCR showed that the 9 pyroptosis-related lncRNAs could be used as prognostic indicators. Conclusion A novel risk model based on pyroptosis-related lncRNAs was constructed and demonstrated that these lncRNAs might be used as independent prognostic biomarkers. This will also assist shed light on the COAD prognosis and therapy.
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Xie Y, Wu H, Hu W, Zhang H, Li A, Zhang Z, Ren S, Zhang X. Identification of Hub Genes of Lung Adenocarcinoma Based on Weighted Gene Co-Expression Network in Chinese Population. Pathol Oncol Res 2022; 28:1610455. [PMID: 36032660 PMCID: PMC9399347 DOI: 10.3389/pore.2022.1610455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/11/2022] [Indexed: 11/20/2022]
Abstract
Purpose: Lung adenocarcinoma is one of the most common malignancies. Though some historic breakthroughs have been made in lung adenocarcinoma, its molecular mechanisms of development remain elusive. The aim of this study was to identify the potential genes associated with the lung adenocarcinoma progression and to provide new ideas for the prognosis evaluation of lung adenocarcinoma. Methods: The transcriptional profiles of ten pairs of snap-frozen tumor and adjacent normal lung tissues were obtained by performing RNA-seq. Weighted gene co-expression network analysis (WGCNA) was used to construct free-scale gene co-expression networks in order to explore the associations of gene sets with the clinical features and to investigate the functional enrichment analysis of co-expression genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Set Enrichment Analysis (GSEA) analyses were performed using clusterProfiler. The protein-protein network (PPI) was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and hub genes were identified using Cytohubba in Cytoscape. Transcription factor enrichment analysis was performed by the RcisTarget program in R language. Results: Based on RNA-seq data, 1,545 differentially expressed genes (DEGs) were found. Eight co-expression modules were identified among these DEGs. The blue module exhibited a strong correlation with LUAD, in which ADCY4, RXFP1, AVPR2, CALCRL, ADRB1, RAMP3, RAMP2 and VIPR1 were hub genes. A low expression level of RXFP1, AVPR2, ADRB1 and VIPR1 was detrimental to the survival of LUAD patients. Genes in the blue module enriched in 86 Gene Ontology terms and five KEGG pathways. We also found that transcription factors EGR3 and EXOSC3 were related to the biological function of the blue module. Overall, this study brings a new perspective to the understanding of LUAD and provides possible molecular biomarkers for prognosis evaluation of LUAD.
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Affiliation(s)
- Yuning Xie
- School of Public Health, North China University of Science and Technology, Tangshan, China
| | - Hongjiao Wu
- School of Public Health, North China University of Science and Technology, Tangshan, China
| | - Wenqian Hu
- School of Public Health, North China University of Science and Technology, Tangshan, China
| | - Hongmei Zhang
- School of Public Health, North China University of Science and Technology, Tangshan, China
| | - Ang Li
- School of Public Health, North China University of Science and Technology, Tangshan, China
| | - Zhi Zhang
- Affiliated Tangshan Gongren Hospital, North China University of Science and Technology, Tangshan, China
| | - Shuhua Ren
- Affiliated Tangshan Gongren Hospital, North China University of Science and Technology, Tangshan, China
- *Correspondence: Shuhua Ren, ; Xuemei Zhang,
| | - Xuemei Zhang
- School of Public Health, North China University of Science and Technology, Tangshan, China
- College of Life Sciences, North China University of Science and Technology, Tangshan, China
- *Correspondence: Shuhua Ren, ; Xuemei Zhang,
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Identification of fatty acid metabolism-related lncRNAs in the prognosis and immune microenvironment of colon adenocarcinoma. Biol Direct 2022; 17:19. [PMID: 35902970 PMCID: PMC9331591 DOI: 10.1186/s13062-022-00332-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 07/23/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Cancer metabolism is largely altered compared to normal cells. This study aims to explore critical metabolism pathways in colon adenocarcinoma (COAD), and reveal the possible mechanism of their role in cancer progression. METHODS Expression data and sequencing data of COAD samples were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The expression profiles between tumor and normal samples were compared to identify differential metabolism pathways through single sample gene set enrichment analysis. RESULTS Fatty acid synthesis was identified as a key metabolism pathway in COAD. Based on fatty acid-related lncRNAs, two molecular subtypes (C1 and C2) were defined. C2 subtype with worse prognosis had higher immune infiltration and higher expression of immune checkpoints. Five transcription factors (TFs) including FOS, JUN, HIF1A, STAT3 and STAT2 were highly expressed in C2 subtype. Five fatty acid-related lncRNAs were identified to be biomarkers for predicting COAD prognosis. Finally, further experients showed that knockdown of lncRNA PAXIP1-AS1 decreased the triglyceride content and the fatty acid synthase and acetyl-CoA carboxylase 1 expressions, which suggested that lncRNA PAXIP1-AS1 plays an important role in fatty acid metabolism of COAD. CONCLUSIONS This study demonstrated that fatty acid synthesis was greatly altered in COAD. Fatty acid-related lncRNAs were speculated to be involved in cancer progression through associating with TFs. The five screened TFs may serve as new drug targets for treating COAD.
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25
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Wang Z, Zhang Z, Zhang K, Zhou Q, Chen S, Zheng H, Wang G, Cai S, Wang F, Li S. Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer. Front Oncol 2022; 12:881953. [PMID: 35600382 PMCID: PMC9117699 DOI: 10.3389/fonc.2022.881953] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Background Glycerolipid metabolism is involved in the genesis and progression of colon cancer. The current study aims at exploring the prognostic value and potential molecular mechanism of glycerolipid metabolism-related genes in colon cancer from the perspective of multi-omics. Methods Clinical information and mRNA expression data of patients with colon cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-sample gene set enrichment analysis (ssGSEA) was applied to calculate the glycerolipid metabolism-related gene enrichment score (GLMS). Univariable and multivariable Cox regression analyses were used to study the prognostic value of GLMS in TCGA-COAD and GSE39582 cohorts. The molecular mechanism of the prognostic factor was investigated via immune cell infiltration estimation and correlation analysis of cancer hallmark pathways. Single-cell transcriptomic dataset GSE146771 was used to identify the cell populations which glycerolipid metabolism targeted on. Results The GLMS was found to be associated with tumor location and consensus molecular types (CMSs) of colon cancer in TCGA-COAD cohort (P < 0.05). Patients in the low-GLMS group exhibited poorer overall survival (OS) in TCGA cohort (P = 0.03; HR, 0.63; 95% CI, 0.42-0.94), which was further validated in the GSE39582 dataset (P < 0.001; HR, 0.57; 95% CI, 0.43-0.76). The association between the GLMS and OS remained significant in the multivariable analysis (TCGA cohort: P = 0.04; HR, 0.64; 95% CI, 0.42-0.98; GSE39582 cohort: P < 0.001; HR, 0.60; 95% CI, 0.45-0.80). The GLMS was positively correlated with cancer hallmark pathways including bile acid metabolism, xenobiotic metabolism, and peroxisome and negatively correlated with pathways such as interferon gamma response, allograft rejection, apoptosis, and inflammatory response (P < 0.05). Increased immune infiltration and upregulated expression of immune checkpoints were observed in patients with lower GLMS (P < 0.05). Single-cell datasets verified the different distribution of GLMS in cell subsets, with significant enrichment of GLMS in malignant cells and Tprolif cells. Conclusion We demonstrated that GLMS was a potential independent prognostic factor for colon cancer. The GLMS was also correlated with several cancer hallmark pathways, as well as immune microenvironment.
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Affiliation(s)
- Zhiyu Wang
- Department of Medical Oncology, Hebei Key Laboratory of Cancer Radiotherapy and Chemotherapy, Affiliated Hospital of Hebei University, Baoding, China
| | - Zhuoqi Zhang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, China
| | - Ke Zhang
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qiaoxia Zhou
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Sidong Chen
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Hao Zheng
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Guoqiang Wang
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Shangli Cai
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Fujing Wang
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shenglong Li
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
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Li X, Guo L, Zhang W, He J, Ai L, Yu C, Wang H, Liang W. Identification of Potential Molecular Mechanism Related to Infertile Endometriosis. Front Vet Sci 2022; 9:845709. [PMID: 35419445 PMCID: PMC8995652 DOI: 10.3389/fvets.2022.845709] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 02/28/2022] [Indexed: 11/17/2022] Open
Abstract
Objectives In this research, we aim to explore the bioinformatic mechanism of infertile endometriosis in order to identify new treatment targets and molecular mechanism. Methods The Gene Expression Omnibus (GEO) database was used to download MRNA sequencing data from infertile endometriosis patients. The “limma” package in R software was used to find differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was used to classify genes into modules, further obtained the correlation coefficient between the modules and infertility endometriosis. The intersection genes of the most disease-related modular genes and DEGs are called gene set 1. To clarify the molecular mechanisms and potential therapeutic targets for infertile endometriosis, we used Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) enrichment, Protein-Protein Interaction (PPI) networks, and Gene Set Enrichment Analysis (GSEA) on these intersecting genes. We identified lncRNAs and miRNAs linked with infertility and created competing endogenous RNAs (ceRNA) regulation networks using the Human MicroRNA Disease Database (HMDD), mirTarBase database, and LncRNA Disease database. Results Firstly, WGCNA enrichment analysis was used to examine the infertile endometriosis dataset GSE120103, and we discovered that the Meorangered1 module was the most significantly related with infertile endometriosis. The intersection genes were mostly enriched in the metabolism of different amino acids, the cGMP-PKG signaling pathway, and the cAMP signaling pathway according to KEGG enrichment analysis. The Meorangered1 module genes and DEGs were then subjected to bioinformatic analysis. The hub genes in the PPI network were performed KEGG enrichment analysis, and the results were consistent with the intersection gene analysis. Finally, we used the database to identify 13 miRNAs and two lncRNAs linked to infertility in order to create the ceRNA regulatory network linked to infertile endometriosis. Conclusion In this study, we used a bioinformatics approach for the first time to identify amino acid metabolism as a possible major cause of infertility in patients with endometriosis and to provide potential targets for the diagnosis and treatment of these patients.
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Affiliation(s)
- Xiushen Li
- Department of Obstetrics and Gynecology, Shenzhen University General Hospital, Shenzhen, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen, China
- Shenzhen Key Laboratory, Shenzhen University General Hospital, Shenzhen, China
| | - Li Guo
- School of Pharmaceutical Sciences, Health Science Center, Shenzhen University, Shenzhen, China
| | - Weiwen Zhang
- Department of Obstetrics and Gynecology, Shenzhen University General Hospital, Shenzhen, China
| | - Junli He
- Department of Pediatrics, Shenzhen University General Hospital, Shenzhen, China
| | - Lisha Ai
- Department of Teaching and Research, Shenzhen University General Hospital, Shenzhen, China
| | - Chengwei Yu
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
- Chinese Academy of Sciences (CAS) Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
- Chengwei Yu
| | - Hao Wang
- Department of Obstetrics and Gynecology, Shenzhen University General Hospital, Shenzhen, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen, China
- Shenzhen Key Laboratory, Shenzhen University General Hospital, Shenzhen, China
- Hao Wang
| | - Weizheng Liang
- Department of Pediatrics, Shenzhen University General Hospital, Shenzhen, China
- *Correspondence: Weizheng Liang
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Qin Y, Li M, Lin Q, Pan X, Liang Y, Huang Z, Liu Z, Huang L, Fang M. Colorectal Cancer Cell Differentiation Trajectory Predicts Patient Immunotherapy Response and Prognosis. Cancer Control 2022; 29:10732748221121382. [PMID: 36036380 PMCID: PMC9421035 DOI: 10.1177/10732748221121382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Objectives This study aimed to investigate the differentiation state and clinical significance of colorectal cancer cells, as well as to predict the immune response and prognosis of patients based on differentiation-related genes of colorectal cancer. Introduction Colorectal cancer cells exhibit different differentiation states under the influence of the tumor microenvironment, which determines the cell fates. Methods We combined single-cell sequencing (scRNA-seq) data from The Cancer Genome Atlas source with extensive transcriptome data from the Gene Expression Omnibus database. We obtained colorectal cancer differentiation-related genes using cell trajectory analysis and developed a colorectal cancer differentiation-related gene based molecular typing and prognostic model to predict the immune response and prognosis of patients with colorectal cancer. Results We identified 5 distinct cell differentiation subsets and 620 colorectal cancer differentiation-related genes. Colorectal cancer differentiation-related genes were significantly associated with metabolism, angiogenesis, and immunity. We separated patients into 3 subtypes based on colorectal cancer differentiation-related gene expression in the tumor and found differences among the different subtypes in immune infiltration status, immune checkpoint gene expression, clinicopathological features, and overall survival. Immunotherapeutic interventions involving a highly expressed immune checkpoint blockade may be selectively effective in the corresponding cancer subtypes. We built a risk score prediction model (5-year AUC: .729) consisting of the 4 most important predictors of survival (TIMP1, MMP1, LGALS4, and ITLN1). Finally, we generated and validated a nomogram consisting of the risk score and clinicopathological variables. Conclusion This study highlights the significance of genes involved in cell differentiation for clinical prognosis and immunotherapy in patients and provides prospective therapeutic targets for colorectal cancer.
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Affiliation(s)
- Yuling Qin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China.,Guangxi Clinical Research Center for Anesthesiology, China.,Guangxi Engineering Research Center for Tissue & Organ Injury and Repair Medicine, China.,Guangxi Key Laboratory for Basic Science and Prevention of Perioperative Organ Disfunction, China
| | - Meiqin Li
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China
| | - Qiumei Lin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China
| | - Xiaolan Pan
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China
| | - Yihua Liang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China
| | - Zhaodong Huang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China
| | - Zhimin Liu
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China
| | - Lingsha Huang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China
| | - Min Fang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, China.,Guangxi Clinical Research Center for Anesthesiology, China.,Guangxi Engineering Research Center for Tissue & Organ Injury and Repair Medicine, China.,Guangxi Key Laboratory for Basic Science and Prevention of Perioperative Organ Disfunction, China
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Xiao Y, Zhang G, Wang L, Liang M. Exploration and validation of a combined immune and metabolism gene signature for prognosis prediction of colorectal cancer. Front Endocrinol (Lausanne) 2022; 13:1069528. [PMID: 36518242 PMCID: PMC9742469 DOI: 10.3389/fendo.2022.1069528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 11/14/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is still one of the most frequently diagnosed malignancy around the world. The complex etiology and high heterogeneity of CRC necessitates the identification of new reliable signature to identify different tumor prognosis, which may help more precise understanding of the molecular properties of CRC and identify the appropriate treatment for CRC patients. In this study, we aimed to identify a combined immune and metabolism gene signature for prognosis prediction of CRC from large volume of CRC transcriptional data. METHODS Gene expression profiling and clinical data of HCC samples was retrieved from the from public datasets. IRGs and MRGs were identified from differential expression analysis. Univariate and multivariate Cox regression analysis were applied to establish the prognostic metabolism-immune status-related signature. Kaplan-Meier survival and receiver operating characteristic (ROC) curves were generated for diagnostic efficacy estimation. Real-time polymerase chain reaction (RT-PCR), Western blot and immunohistochemistry (IHC) was conducted to verified the expression of key genes in CRC cells and tissues. RESULTS A gene signature comprising four genes (including two IRGs and two MRGs) were identified and verified, with superior predictive performance in discriminating the overall survival (OS) of high-risk and low-risk compared to existing signatures. A prognostic nomogram based on the four-gene signature exhibited a best predictive performance, which enabled the prognosis prediction of CRC patients. The hub gene ESM1 related to CRC were selected via the machine learning and prognostic analysis. RT-PCR, Western blot and IHC indicated that ESM1 was high expressed in tumor than normal with superior predictive performance of CRC survival. CONCLUSIONS A novel combined MRGs and IRGs-related prognostic signature that could stratify CRC patients into low-and high- risk groups of unfavorable outcomes for survival, was identified and verified. This might help, to some extent, to individualized treatment and prognosis assessment of CRC patients. Similarly, the mining of key genes provides a new perspective to explore the molecular mechanisms and targeted therapies of CRC.
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Affiliation(s)
- Yitai Xiao
- Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong, China
- *Correspondence: Yitai Xiao, ; Mingzhu Liang,
| | - Guixiong Zhang
- Department of Interventional Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Lizhu Wang
- Department of Radiology, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Mingzhu Liang
- Department of Radiology, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong, China
- *Correspondence: Yitai Xiao, ; Mingzhu Liang,
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29
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A Novel Cancer Stemness-Related Signature for Predicting Prognosis in Patients with Colon Adenocarcinoma. Stem Cells Int 2021; 2021:7036059. [PMID: 34691191 PMCID: PMC8536464 DOI: 10.1155/2021/7036059] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/13/2021] [Indexed: 12/19/2022] Open
Abstract
Objective To explore the cancer stemness features and develop a novel cancer stemness-related prognostic signature for colon adenocarcinoma (COAD). Methods We downloaded the mRNA expression data and clinical data of COAD from TCGA database and GEO database. Stemness index, mRNAsi, was utilized to investigate cancer stemness features. Weighted gene coexpression network analysis (WGCNA) was used to identify cancer stemness-related genes. Univariate and multivariate Cox regression analyses were applied to construct a prognostic risk cancer stemness-related signature. We then performed internal and external validation. The relationship between cancer stemness and COAD immune microenvironment was investigated. Results COAD patients with higher mRNAsi score or EREG-mRNAsi score have significant longer overall survival (OS). We identified 483 differently expressed genes (DEGs) between the high and low mRNAsi score groups. We developed a cancer stemness-related signature using fifteen genes (including RAB31, COL6A3, COL5A2, CCDC80, ADAM12, VGLL3, ECM2, POSTN, DPYSL3, PCDH7, CRISPLD2, COLEC12, NRP2, ISLR, and CCDC8) for prognosis prediction of COAD. Low-risk score was associated with significantly preferable OS in comparison with high-risk score, and the area under the ROC curve (AUC) for OS prediction was 0.705. The prognostic signature was an independent predictor for OS of COAD. Macrophages, mast cells, and T helper cells were the vital infiltration immune cells, and APC costimulation and type II IFN response were the vital immune pathways in COAD. Conclusions We developed and validated a novel cancer stemness-related prognostic signature for COAD, which would contribute to understanding of molecular mechanism in COAD.
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